plot_1d_excess

lstchain.visualization.plot_dl2.plot_1d_excess(named_datasets, lima_significance, x_label, x_cut, ax=None, x_range_min=0, x_range_max=2, n_bins=100, opacity=0.2, color_map_name='Set1')

Plot one-dimensional distribution of signal and backgound events Color maps: https://matplotlib.org/gallery/color/colormap_reference.html

Parameters:

named_datasets: Array of datasets to plot in a following form: (<dataset label>, data, overall

scale factor)

lima_significance: Li&Ma significance of observation

x_label: X-axis label

x_cut: X cut value

ax: `matplotlib.pyplot.axes` or None

x_range_min: Bottom value of X

x_range_max: Top value of X

n_bins: Number of histogram bins along X axis

opacity: Plot opaacity

color_map_name: Matplotlib colormap name

Returns:

ax: matplotlib.pyplot.axes